Abstract: Disclosed is a computer-implemented method of generating a dental model based on an objective function output, including creating an objective function including at least one quality estimation function which trains at least one machine learning method that generates quality estimation output, and an objective function output is the output of the objective function providing a model as an input data to the objective function and generating model-related objective function output; and modifying the model based on the model-related objective function output to transform the model to a generated model, wherein the generated model is the dental model.

Abstract: The present disclosure relates to a computer-implemented method for designing a dental prosthesis. A first step of the method may be to obtain a digital 3D representation of a surface, the surface including at least a part of a preparation surface adapted to receive the dental prosthesis, wherein the preparation surface includes a visible part and a hidden part. A second step of the method may be to determine at least one part of a surface of the dental prosthesis using a statistical design model, wherein the at least one part is determined independent of any knowledge or estimate of the hidden part of the preparation surface. A final step of the method may be to design the dental prosthesis wherein the surface of the dental prosthesis includes the at least one part.

Abstract: A computer-implemented method of generating a dental model based on an objective function output, including creating an objective function including at least one quality estimation function which trains at least one machine learning method that generates quality estimation output, and an objective function output is the output of the objective function providing a model as an input data to the objective function and generating model-related objective function output; and modifying the model based on the model-related objective function output to transform the model to a generated model, wherein the generated model is the dental model.

Abstract: A computer-implemented method of generating a dental model based on an objective function output, including creating an objective function including at least one quality estimation function which trains at least one machine learning method that generates quality estimation output, and an objective function output is the output of the objective function providing a model as an input data to the objective function and generating model-related objective function output; and modifying the model based on the model-related objective function output to transform the model to a generated model, wherein the generated model is the dental model.

Abstract: Disclosed is an optical coherence tomography scanner and a method for recording sub-surface scans of an object, wherein a position encoder is arranged in the path of the probing beam of an interferometric system. The encoder pattern is detected in a sequence of A scans at generated for different probing beam positions on the scanned object, the probing beam position and/or inclination for at least one A scan of said sequence of A scans is deducing based on the detected encoder pattern, and the sub-surface scan of the object is generated based on the sequence of A scans taking into account the deduced probing beam position and/or inclination.

Abstract: Disclosed is an optical coherence tomography scanner and a method for recording sub-surface scans of an object, wherein a position encoder is arranged in the path of the probing beam of an interferometric system. The encoder pattern is detected in a sequence of A scans at generated for different probing beam positions on the scanned object, the probing beam position and/or inclination for at least one A scan of said sequence of A scans is deducing based on the detected encoder pattern, and the sub-surface scan of the object is generated based on the sequence of A scans taking into account the deduced probing beam position and/or inclination.